Robust FA based on a robust covariance matrix. Robust FA are obtained by replacing the classical covariance matrix by a robust covariance estimator. This can be one of the available in `rrcov`

estimators, i.e., MCD, OGK, M, S, SDE, or MVE estimator.

Objects can be created by calls of the form `new("FaCov", ...)`

.
But the usual way of creating `FaCov`

objects is a call to the function `FaCov`

which serves as a constructor.

`call`

:Object of class

`"language"`

an unevaluated function call`converged`

:Object of class

`"Ulogical"`

a logical character indicates whether the iterations converged`loadings`

:Object of class

`"matrix"`

the matrix of variable loadings`uniquenesses`

:Object of class

`"vector"`

the uniquenesses computed`covariance`

:Object of class

`"matrix"`

the covariance matrix`correlation`

:Object of class

`"matrix"`

the correlation matrix`usedMatrix`

:Object of class

`"matrix"`

the used matrix (running matrix)`criteria`

:Object of class

`"Unumeric"`

. The results of the optimization: the value of the negative log-likelihood and information on the iterations used.`factors`

:Object of class

`"numeric"`

the number of factors`dof`

:Object of class

`"Unumeric"`

. The number of degrees of freedom of the factor analysis model.`method`

:Object of class

`"character"`

. The method: one of "mle", "pca", and "pfa".`scores`

:Object of class

`"Umatrix"`

. If requested, a matrix of scores.`scoresMethod`

:Object of class

`"character"`

. The scores method: one of "none", "regression", and "Bartlett".`STATISTIC`

:Object of class

`"Unumeric"`

. The significance-test statistic, if it can be computed.`PVAL`

:Object of class

`"Unumeric"`

. The significance-test P value, if it can be computed.`n.obs`

:Object of class

`"Unumeric"`

. The number of observations if available.`center`

:Object of class

`"Uvector"`

. The center of the data.`eigenvalues`

:Object of class

`"vector"`

the eigenvalues`cov.control`

:Object of class

`"UCovControl"`

. Record the cov control method.

Class `"FaRobust"`

, directly.
Class `"Fa"`

, by class "FaRobust", distance 2.

No methods defined with class "FaCov" in the signature.

Ying-Ying Zhang (Robert) robertzhangyying@qq.com

Zhang, Y. Y. (2013), An Object Oriented Solution for Robust Factor Analysis.

`FaClassic-class`

, `FaCov-class`

, `FaRobust-class`

, `Fa-class`

1 | ```
showClass("FaCov")
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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